Matteo Grazioso is a Ph.D. Student in Computer Science at Ca’ Foscari University of Venice (Department of Environmental Sciences, Informatics and Statistics).

His primary research focuses on Interpretable and Fairness-preserving AI for High-Risk applications, where he explores the design of trustworthy AI systems, ensuring that Machine Learning models in high-stakes domains are both transparent and ethically aligned.

Matteo’s research interests lie at the intersection of Computational Intelligence, Machine Learning, Interpretable AI, High-Performance Computing, Evolutionary Drug Discovery, and Optimization Algorithms. He holds a Master’s Degree in Computer Science – Artificial Intelligence and Data Engineering –, graduated summa cum laude from Ca’ Foscari University of Venice, where he also served as a Research Grant Holder.

In parallel with his doctoral studies, Matteo serves as a Scientific Associate at the Italian National Institute of Nuclear Physics (INFN), Milano Bicocca Division, and is a Visiting Ph.D. Student at the University of Milano-Bicocca (Department of Informatics, Systems and Communication).

He is an active member of the FRACTALS Research Group (Fair and Responsible Algorithms for Complex-systems, Therapeutics, Astrophysics and Life-Sciences), where he contributes to interdisciplinary research on trustworthy AI, computational intelligence, and high-risk applications.

He is an active member of the IEEE and the IEEE Computational Intelligence Society (CIS). Within the IEEE CIS, he contributes to the Advanced Representation in Biological and Medical Search and Optimization (ARBM) Task Force under the Bioinformatics & Bioengineering Technical Committee (BBTC), and the AI Governance, Regulation and Compliance (AIRC) Task Force under the Ethical, Legal, Social, Environmental and Human Dimensions of AI/CI Technical Committee (SHIELD).

For further information, please visit his personal website at matteograzioso.com or connect via LinkedIn.